Commercial organisations commonly use operational research tools to solve vehicle routing problems. This practice is less commonplace in charity and voluntary organisations. In this paper, we provide an elementary app...Commercial organisations commonly use operational research tools to solve vehicle routing problems. This practice is less commonplace in charity and voluntary organisations. In this paper, we provide an elementary approach for solving the Vehicle Routing Problem (VRP) that we believe can be easily implemented in these types of organisations. The proposed model leverages mixed integer linear programming to optimize the pickup sequence of all customers, each with distinct time windows and locations, transporting them to a final destination using a fleet of vehicles. To ensure ease of implementation, the model utilises Python, a user-friendly programming language, and integrates with the Google Maps API, which simplifies data input by eliminating the need for manual entry of travel times between locations. Troubleshooting methods are incorporated into the model design to ensure easy debugging of the model’s infeasibilities. Additionally, a computation time analysis is conducted to evaluate the efficiency of the code. A node partitioning approach is also discussed, which aims to reduce computational times, especially when handling larger datasets, ensuring this model is realistic and practical for real-world application. By implementing this optimized routing strategy, logistics companies or organisations can expect significant improvements in their day-to-day operations, with minimal computational cost or need for specialised expertise. This includes reduced travel times, minimized fuel consumption, and thus lower operational costs, while ensuring punctuality and meeting the demands of all passengers.展开更多
Transportation is the lifeblood of a modern metropolis.Accessibility generally refers to the interconnection between nodes in a regional traffic network.The purpose of the paper is to obtain more realistic and accurat...Transportation is the lifeblood of a modern metropolis.Accessibility generally refers to the interconnection between nodes in a regional traffic network.The purpose of the paper is to obtain more realistic and accurate measures of travel speed and to study the road traffic accessibility potential in cities.This study proposes a method for analyzing road traffic accessibility potential which is based on the average travel speed to city centers in off-peak times and which ranks 80 cities around the world.Based on the Suomi National Polar-Orbiting Partnership satellite’s visible-infrared imaging radiometer suite(NPP-VIIRS)night-time light data,urban built-up areas and city centers were extracted.Further,with the aid of the Google Maps application programming interface(API)network crawling technique,travel times and travel distances for several optimal routes to city centers by car were obtained.Feasible proposals for improving road traffic accessibility and planning urban transportation in different cities are presented.The proposed method offers a new possibility of analyzing traffic accessibility using internet data and geo-spatial methods.展开更多
文摘Commercial organisations commonly use operational research tools to solve vehicle routing problems. This practice is less commonplace in charity and voluntary organisations. In this paper, we provide an elementary approach for solving the Vehicle Routing Problem (VRP) that we believe can be easily implemented in these types of organisations. The proposed model leverages mixed integer linear programming to optimize the pickup sequence of all customers, each with distinct time windows and locations, transporting them to a final destination using a fleet of vehicles. To ensure ease of implementation, the model utilises Python, a user-friendly programming language, and integrates with the Google Maps API, which simplifies data input by eliminating the need for manual entry of travel times between locations. Troubleshooting methods are incorporated into the model design to ensure easy debugging of the model’s infeasibilities. Additionally, a computation time analysis is conducted to evaluate the efficiency of the code. A node partitioning approach is also discussed, which aims to reduce computational times, especially when handling larger datasets, ensuring this model is realistic and practical for real-world application. By implementing this optimized routing strategy, logistics companies or organisations can expect significant improvements in their day-to-day operations, with minimal computational cost or need for specialised expertise. This includes reduced travel times, minimized fuel consumption, and thus lower operational costs, while ensuring punctuality and meeting the demands of all passengers.
基金supported by the Zhejiang Provincial Natural Science Foundation of China(No.LZJWY22E090002)the Zhejiang Provincial Water Conservancy Science and Technology Plan Project(No.RC2141),China。
文摘Transportation is the lifeblood of a modern metropolis.Accessibility generally refers to the interconnection between nodes in a regional traffic network.The purpose of the paper is to obtain more realistic and accurate measures of travel speed and to study the road traffic accessibility potential in cities.This study proposes a method for analyzing road traffic accessibility potential which is based on the average travel speed to city centers in off-peak times and which ranks 80 cities around the world.Based on the Suomi National Polar-Orbiting Partnership satellite’s visible-infrared imaging radiometer suite(NPP-VIIRS)night-time light data,urban built-up areas and city centers were extracted.Further,with the aid of the Google Maps application programming interface(API)network crawling technique,travel times and travel distances for several optimal routes to city centers by car were obtained.Feasible proposals for improving road traffic accessibility and planning urban transportation in different cities are presented.The proposed method offers a new possibility of analyzing traffic accessibility using internet data and geo-spatial methods.
